Building a Model Context Protocol (MCP) Server for Live Web Scraping & Agent Context

The Model Context Protocol (MCP) is presented as an open client-server standard that lets AI applications connect to external tools and sources through JSON-RPC, reducing reliance on vendor-specific integrations. The text argues that AI agents benefit from live web access but that raw HTML is inefficient and potentially unreliable because it contains large amounts of boilerplate, scripts, and styling, whereas sanitized Markdown can substantially reduce token use while preserving meaningful structure. It outlines a TypeScript-based MCP server that exposes a web-scraping tool, sends URL requests to Context.dev’s Markdown Scrape API, and returns cleaned content to MCP-compatible hosts such as Claude Desktop. The discussion recommends using managed scraping infrastructure instead of operating local browser automation and proxy systems, particularly for JavaScript-heavy sites and anti-bot protections. It also highlights security considerations including SSRF protections, mitigation of indirect prompt injection, and chunking or pagination for oversized pages, while positioning Context.dev as a provider of web, product, and brand context infrastructure for enterprise AI agents.

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